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Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗

DOE OSTI2012

Technical Note: Improved implementation of doppler broadening in MCNP5

Purpose: Incoherent scattering has a substantial effect on spectroscopic measurements and simulations. Many general-purpose Monte Carlo codes include models that account for the effects of bound electrons on incoherent scattering, including Doppler broadening (DB). This work investigates the DB model used in the Monte Carlo N-particle transport code (MCNP5). Methods: Simulations were run with three versions of MCNP5: v1.51, v1.60, and a modified form of v1.60 (v1.60m). All simulations used the MCPLIB04 photon data library, which presents the electron subshell data for incoherent scattering in the form of a probability density function. In v1.60m, the source code was altered to sample the electron subshell from a cumulative density function instead. Each version of the code was tested using an identical set of simulations that investigated DB in a slab of silicon at scattering angles of 15 Degree-Sign , 30 Degree-Sign , and 45 Degree-Sign . For each angle, simulations were run for multiple energies between 200 keV and 800 keV. The spectrum of singly-scattered photons at the exit of the slab was scored. Spectra were analytically calculated for comparison. Results: In v1.51, DB was modeled for incident photon energies below 760 keV, 384 keV, and 260 keV at scattering angles of 15 Degree-Sign , 30 Degree-Sign , and 45 Degree-Sign , respectively. Above these energy thresholds, v1.51 did not model DB. The spectra calculated using v1.60 and v1.60m exhibited DB for all energy-angle combinations; however, v1.60m, exhibited more energy broadening than did v1.60. The spectra calculated with v1.60m agreed with the analytical calculations. Conclusions: MCNP5 v1.51 and v1.60 model partial broadening when used with the MCPLIB04 data library. MCNP5 v1.60m models DB more accurately due to the form of the electron subshell data. In response to these results, Los Alamos National Laboratory has released a new photon data library, MCPLIB84, that presents the electron subshell data in cumulative distribution form. MCNP5 v1.60 should be used with this library when incoherent scattering has a significant impact on simulation results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

MarpoDB: An open registry for Marchantia polymorpha genetic parts

Marchantia polymorpha is an extant relative of the earliest terrestrial plants and has attracted a substantial interest as a model organism for evolutionary and developmental studies. Given its relatively simple genome, compact gene families, simple morphology, ease of propagation and transformation, M. polymorpha is becoming a promising platform for plant synthetic biology. Modular genetic parts have been essential for development of synthetic biology approaches, so we sought to design an engineering oriented database for M. polymorpha genetic parts where each gene is a standalone functional unit. MarpoDB is a database of M. polymorpha genes and genetic parts, which is tailored to become an integral tool for a synthetic biology workflow. Among its features are precompiled cross-database querying to InterPro, Pfam signatures and non-redundant Viridiplantae BLAST annotations; BLAST querying to M. polymorpha genes; sequence export in GenBank format; recoding of sequences to the common syntax for type IIS assembly and exchange of DNA parts; and a minimalistic, intuitive and interactive user interface for gene models and sequence exploration. Furthermore, we have implemented user input to encourage feedback, collaboration and exchange between the MarpoDB community. MarpoDB source-code is released on GitHub to promote development of computational tools for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

SANSMIC v.1.0

SAND2024-01036O The updated Sandia Solution Mining Code (SANSMIC) modeling software models the dissolution of underground salt cavern walls due to raw-water injection (leaching), assuming an oil blanket. A previous version of this software modeled the impacts of leaching at the Strategic Petroleum Reserve and has been used in research for several decades, but the source code was not available. The new version will enhance current research as additional subsurface storage of energy in solution-mined caverns increases. It will also allow research reproducibility by making the software available to the wider research community. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, David↗

NASA NTRS1988

Ada/POSIX binding: A focused Ada investigation

NASA is seeking an operating system interface definition (OSID) for the Space Station Program (SSP) in order to take advantage of the commercial off-the-shelf (COTS) products available today and the many that are expected in the future. NASA would also like to avoid the reliance on any one source for operating systems, information system, communication system, or instruction set architecture. The use of the Portable Operating System Interface for Computer Environments (POSIX) is examined as a possible solution to this problem. Since Ada is already the language of choice for SSP, the question of an Ada/POSIX binding is addressed. The intent of the binding is to provide access to the POSIX standard operation system (OS) interface and environment, by which application portability of Ada applications will be supported at the source code level. A guiding principle of Ada/POSIX binding development is a clear conformance of the Ada interface with the functional definition of POSIX. The interface is intended to be used by both application developers and system implementors. The objective is to provide a standard that allows a strictly conforming application source program that can be compiled to execute on any conforming implementation. Special emphasis is placed on first providing those functions and facilities that are needed in a wide variety of commercial applications

Legrand, Sue↗

DOE OSTI2014

Task 6 - Subtask 1: PNNL Visit by JAEA Researchers to Evaluate the Feasibility of the FLESCOT Code for the Future JAEA Use for the Fukushima Surface Water Environmental Assessment

Four Japan Atomic Energy Agency (JAEA) researchers visited Pacific Northwest National Laboratory (PNNL) for seven working days and have evaluated the suitability and adaptability of FLESCOT to a JAEA’s supercomputer system to effectively simulate cesium behavior in dam reservoirs, river mouths, and coastal areas in Fukushima contaminated by the Fukushima Daiichi nuclear accident. PNNL showed the following to JAEA visitors during the seven-working day period: FLESCOT source code; User’s manual; FLESCOT description – Program structure – Algorism – Solver – Boundary condition handling – Data definition – Input and output methods – How to run. During the visit, JAEA had access to FLESCOT to run with an input data set to evaluate the capacity and feasibility of adapting it to a JAEA super computer with massive parallel processors. As a part of this evaluation, PNNL ran FLESCOT for sample cases of the contaminant migration simulation to further describe FLESCOT in action. JAEA and PNNL researchers also evaluated time spent for each subroutine of FLESCOT, and the JAEA researcher implemented some initial parallelization schemes to FLESCOT. Based on this code evaluation, JAEA and PNNL determined that FLESCOT is: applicable to Fukushima lakes/dam reservoirs, river mouth areas, and coastal water; and feasible to implement parallelization for the JAEA supercomputer. In addition, PNNL and JAEA researchers discussed molecular modeling approaches on cesium adsorption mechanisms to enhance the JAEA molecular modeling activities. PNNL and JAEA also discussed specific collaboration of molecular and computational modeling activities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Verified lifting of stencil computations

This paper demonstrates a novel combination of program synthesis and verification to lift stencil computations from low-level Fortran code to a high-level summary expressed using a predicate language. The technique is sound and mostly automated, and leverages counter-example guided inductive synthesis (CEGIS) to find provably correct translations. Lifting existing code to a high-performance description language has a number of benefits, including maintainability and performance portability. For example, our experiments show that the lifted summaries can enable domain specific compilers to do a better job of parallelization as compared to an off-the-shelf compiler working on the original code, and can even support fully automatic migration to hardware accelerators such as GPUs. We have implemented verified lifting in a system called STNG and have evaluated it using microbenchmarks, mini-apps, and real-world applications. Here, we demonstrate the benefits of verified lifting by first automatically summarizing Fortran source code into a high-level predicate language, and subsequently translating the lifted summaries into Halide, with the translated code achieving median performance speedups of 4.1X and up to 24X for non-trivial stencils as compared to the original implementation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

ZEM: Integrated Framework for Real-Time Data and Model Analyses for Robust Environmental Management Decision Making - 16438

Typically environmental management (EM) problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly analysis, assimilation and integration into a series of models with different complexity for various types of model-based analyses. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian-Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is predominantly coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org) and incorporates the MADS computational tools (Model Analysis and Decision Support; http://mads.lanl.gov). We demonstrate the application of ZEM for data and model analyses at the LANL Chromium site. The ZEM framework will be released as open-source code and can be applied to any environmental management site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

WEC-Sim (Wave Energy Converter - SIMulator)

WEC-Sim (Wave Energy Converter SIMulator) is a code developed by Sandia National Laboratories and the National Renewable Energy Laboratory to model wave energy converters (WECs) when they are subject to operational waves. The code is a time-domain modeling tool developed in MATLAB/Simulink using the multi-body dynamics solver SimMechanics. In WEC-Sim, WECs are modeled by connecting rigid bodies to one another with joint or constraint blocks from the WEC-Sim library. WEC-Sim is a publicly available, open-source code to model WECs.

Source record↗

DOE OSTI2024

Human Liver Epithelium Response to HCoV-229E Infection Epigenomics (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-229E) infection alters chromatin accessibility in infected cells only. Sample data was obtained for mock and infected (standard and UV-inactivated) immortalized human liver cells (HuH-7) and collected 24 hrs. post infection. Samples were processed using assay for transposase-accessible chromatin using high-throughput sequencing (ATAC-Seq) and generated bar coded library samples were evaluated for RNA sequencing (RNA-Seq) expression analysis. Processed ATAC-Seq datasets are openly accessible from the download button and contain secondary processed RNA-Seq results files and supporting metadata materials. Data download includes a sample naming key, infection titer metadata, normalized counts, and relevant computational source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

WEC-Sim (Wave Energy Converter - SIMulator)

Source record↗

DOE OSTI2021

Optimization Plugin Library

The Optimization Plugin library ("op") is a lightweight general optimization solver interface. The primary purpose of op is to simplify the process of integrating different optimization solvers (serial or parallel) with scalable parallel physics engines. By design it has several features that help make this a reality. The core abstraction interface was developed to encompass a large class of optimization problems in an optimizer-agnostic way. This enables us to describe the optimization problem once and then use a variety of supported "op" optimizers with ideally no code-changes. The abstraction interface is made up of lightweight wrappers that make it easy to integrate with existing simulation codes. This makes integration less intrusive and should minimize changes to existing physics codes. The "op" interface includes an assortment of utility methods that help specify parallel communication patterns as well as methods to convert from optimization-specific interfaces to the more general "op" interface. Lastly a dynamic library linking interface is provided to allow for use of proprietary optimization engines without explicit reference in the source code, along with standard shared library interfaces for opensource engines.

Jekel, CharlesF↗

DOE OSTI2021

Simple, Secure, Internet Delivery of MOOSE-based Applications

Application packaging and distribution are the final steps for delivering software to end-users; both are frequently neglected when creating scientific software. Commercial businesses rely on electronic distribution systems that have rendered disk drives obsolete. Still, national laboratories continue to rely heavily on removable media to distribute and limit access to controlled applications. With increasing concerns of unauthorized copying of sensitive applications, a modern distribution system that utilizes cryptographically secure communication and authentication protocols has been developed. This new distribution system will secure the chain of custody for nuclear software while simultaneously simplifying access to these tools. This report summarizes four primary advancements made toward the secure distribution of Nuclear Energy Advanced Modeling and Simulation (NEAMS)-developed, Multiphysics Object Oriented Simulation Environment (MOOSE)-based applications: application installation, package distribution, automated package building, and distribution of documentation. NEAMS is currently developing more than ten separate applications based on the open-source MOOSE Framework. Distribution of these applications has primarily been accomplished by distributing source code, with end-users compiling the applications themselves. This work created a mechanism where MOOSE applications can be installed in a similar way to any other software. This allows both administrators and end-users simplified access to runnable executables. With this new installation capability, it was then possible to rethink distribution. A new, secure capability for delivering MOOSE-based applications over the internet has been created. This system requires unique cryptographic tokens for authentication, greatly securing the custody chain for software. Once granted access, installation of any NEAMS code can be accomplished with these terminal commands: "conda install ncrc" "ncrc install ncrc-bison." After these two commands (and authenticating) the BISON application will be securely down- loaded from Idaho National Laboratory (INL)’s servers, installed, and ready to use. To enable this new distribution capability to be successful, the open-source Continuous Integration, Verification, Enhancement, and Testing (CIVET) Continuous Integration (CI) capability was augmented to add Continuous Delivery (CD). CD enables the automated building and packaging of MOOSE-based applications as they are modified by development teams, ensuring that our customers can obtain up-to-date versions of the software at any time. The need for instruction on how to use these applications was addressed through modifications to the MOOSE documentation system. The MooseDocs capability, which enables robust documentation of MOOSE-based applications, has been extended to allow both for the installation of documentation and the packaging of documentation with installed applications. Together, these enhancements form the core of a new, secure distribution mechanism for nuclear simulation tools. In concert with the Nuclear Computational Resource Center (NCRC), NEAMS- developed applications will now be straightforward to obtain securely.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

mzapy : An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format

We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of a core library with standard mass spectrometry utilities greatly facilitates fast software development. Here, we present a Python library, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python with minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multi-omics domain. The free and open source mzapy is built with extensibility in mind, and future development will support cloud computing and artificial intelligence/machine learning applications. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Evaluating the Performance of Integer Sum Reduction in SYCL on GPUs

SYCL is a promising programming model for heterogeneous computing—allowing a single-source code to target devices from multiple vendors. One significant task performed on these accelerators is a primitive operation for integer sum reduction. This paper presents several SYCL implementations of integer sum reduction—using atomic functions, shared local memory, vectorized memory accesses and parameterized workload sizes—to compare the performance and maturity of SYCL against open-source vendor-specific implementations of the same reduction. For a sufficiently large number of integers, tuning the parameters of our SYCL implementations achieves 1.4X speedup over the open-source implementations on an Intel UHD630 integrated GPU. The SYCL reduction is 3% faster than the templated reduction in Thrust, and 0.3% faster than the device reduction in CUB on an Nvidia P100 GPU. The SYCL reduction is 1.9% faster than the templated reduction in Thrust, and 0.4% faster than the device reduction in CUB on an Nvidia V100 GPU.

Jin, Zheming↗

DOE OSTI2019

Brief Guide on Outputting Custom Variables in SABLE

Although SABLE supports a wide variety of variable outputs as a default, the code currently does not readily support outputs of custom variables via the 'plot variables' feature in its input file. Workarounds to this issue exist (such as using `spy'), but the distinct convenience and advantage that the 'plot variables' feature provides, such as easy output of results in .exo file format, disappear. The user may explore the source code to correct this issue, but due to the ongoing nature of code building and complexity of the code spanning multiple languages and layers, exploration and correction of the code can be prohibitively difficult. In this memo, a short guide to modify the code to output desired custom variables via 'plot variables' is listed along with an example variable that evaluates the velocity profile before remapping (VELOCITY PREMAP).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness of Variable Renewable Generation

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an innovative, open-source tool for visualizing variable renewable resource forecasts and alerts for significant up- and down-ramps in renewable generation and the consequent system net load. The modular dashboard of RAVIS contains configurable panes for viewing probabilistic time-series forecasts, ramp event alerts on the look-ahead timeline, and spatially resolved resource sites, and forecasts. For comprehensive situational awareness, the tool can add additional data layers from simulation and independent system operator (ISO) market clearing data---including electric line utilization, nodal price, and available generation flexibility---in response to continuously updated renewable forecasts. This paper introduces the RAVIS technology suite employed to provide optimum visualization and flexible design characteristics. The paper also illustrates some use cases of the tool using site-specific solar power forecast data obtained from the IBM Watt-Sun forecasting platform for the California ISO and Midcontinent ISO footprints. The source code for RAVIS is public (https://github.com/ravis-nrel/ravis), and the intended users are forecasters, utility planners, ISO operators, and researchers.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

The Athena++ Adaptive Mesh Refinement Framework: Design and Magnetohydrodynamic Solvers

The design and implementation of a new framework for adaptive mesh refinement calculations are described. It is intended primarily for applications in astrophysical fluid dynamics, but its flexible and modular design enables its use for a wide variety of physics. The framework works with both uniform and nonuniform grids in Cartesian and curvilinear coordinate systems. It adopts a dynamic execution model based on a simple design called a "task list" that improves parallel performance by overlapping communication and computation, simplifies the inclusion of a diverse range of physics, and even enables multiphysics models involving different physics in different regions of the calculation. We describe physics modules implemented in this framework for both nonrelativistic and relativistic magnetohydrodynamics (MHD). These modules adopt mature and robust algorithms originally developed for the Athena MHD code and incorporate new extensions: support for curvilinear coordinates, higher-order time integrators, more realistic physics such as a general equation of state, and diffusion terms that can be integrated with super-time-stepping algorithms. The modules show excellent performance and scaling, with well over 80% parallel efficiency on over half a million threads. The source code has been made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗